Investigating the quality of Spiess-like and SPSA approaches for dynamic OD matrix estimation

Since origin and destination (OD) matrices are not directly observable, indirect procedures have been developed to estimate OD matrices from traffic data. Traffic management must move toward dynamic traffic assignment models because they capture congestion propagation effects. In this context, dynamic OD matrices are needed. This paper first explores the extension of a conventional bilevel analytical static method to the dynamic context, then analyses the solutions obtained regarding both convergence to measured traffic data and structural similarity to an a priori OD matrix. A simulation optimization technique, simultaneous perturbation stochastic approximation (SPSA), is then proposed because its flexibility allows inclusion of traffic counts (as in Spiess method) and emerging information and communications technology (ICT) traffic measurements. The performances of these two types of algorithms are analyzed in detail, focussing on faults of classical convergence measures to obtain an estimated dynamic OD matrix structurally similarity to the a priori OD matrix and pros and cons of variants of selected methods.

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  • English

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  • Accession Number: 01767784
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 29 2021 3:00PM